Research Activities

Project Abstract

For three decades satellite remote sensing instruments operating at visible, near-infrared, and microwave wavelengths have measured snow properties. In all snow products, and in remote sensing in general, there is a tradeoff between spatial resolution and swath width (and thus frequency of observations). Because most hydrologic applications require regular, frequent measurements, the instruments that provide the bulk of the data used have been AVHRR and MODIS in the optical part of the spectrum, with spatial resolutions of 1.1km and 500m at nadir, and the passive microwave sensors, with spatial resolutions of tens of kilometers.

Because snow-covered area usually varies at a spatial scale finer than that of the resolution of the remote sensing instrument (i.e., the ground instantaneous field-of-view), this subpixel heterogeneity introduces artifacts into the measurements. The sensors usually measure radiation reflected or emitted from a mixture of snow, rock, soil, and vegetation. We contend that the errors introduced by subpixel heterogeneity can be systematic, and therefore they are not always eliminated by integrating over many pixels. We propose to develop a new set of products - snow-covered area, albedo, and snow-water equivalence - that fuse optical (MODIS,AVHRR) and microwave data (SSM/R, SSM/I, AMSR-E, and AMSR) and that incorporate spatial heterogeneity into the analysis.

Data product creation and distribution will be provided through a local infrastructure for Earth science product management: a technology suite we call the Earth System Science Server (ES3), an environment for managing the creation, maintenance, updating, and dissemination of Earth science data products. The technology is based on the Microsoft TerraServer and runs on clusters of small computers. In addition to being robust and capacious enough to support public access, the infrastructure is flexible enough to manage the idiosyncratic computing ensembles that typify scientific research